Understanding operations of an entity and taking informed measures requires accessing and processing vast data associated with the entities. Traditionally, entities have relied on surveys or information received from focus groups for accessing such data and processing the data manually. This requires a lot of time and effort both in finding the right people, who are well aware about the entity to administer the survey and in conducting the survey/focus groups. Also, relying on survey and focus groups to collect data limits the number of entities that can be studied at a time. Further, the results from such methods may be biased as in case of moderator bias (moderator influencing the focus group participants with their own views), or by the sample set of the survey. Yet further, the results obtained by administering the survey on people who are aware of an entity ‘X’ cannot be extended to measure critical data of another entity ‘Y’. Therefore the survey needs to be carried for each entity being studied. Furthermore, with the emergence of social media, various social media platforms are considered as an effective base for analyzing user's feedback. However, processing voluminous and complex information separately for different entities of different industries often causes wastage of time and resources and strains the infrastructure that supports the information, moreso, if an entity is within the same industry. This further leads to tedious and time consuming efforts, apart from facing issues of redundant information or omission of critical data associated with the entities. Therefore, conventional methods are, disadvantageously, highly effort intensive and require human interpretation at several stages of analysis and processing of data. To add to it, taking cognizance of real-time changes in data makes the entire process even more complicated, time-consuming, prone to loopholes and demanding increased overhead.
In light of the above drawbacks, there is a need for a system and method that provides for a holistic measure of critical data associated with entities with minimum human involvement. There is a need for a system and method that computes critical data of entities belonging to any industry efficiently and provides faster results to measure the reputation of the entities. Also, there is a need for a system and method that provides for a tool that can be reused with minimal effort for computing critical data associated with different entities with enhanced accuracy.